基于独立成份分析的MPSK信号调制制式自动识别

针对低信噪比情况下传统的MPSK信号识别算法效率不高的问题,提出一种基于快速独立成份分析(FICA)的MPSK信号非监督识别算法.该方法借助快速独立成份分析提取具有不同分布特征的信号分量作为最大似然分类器的识别特征.实验结果表明,此算法在低信噪情况下能有效地分离信号与噪声分量,挖掘有用信息,实现对MPSK信号的高精度自动识别.

MPSK Signals Modulation Auto-recognition Based on Independent Component Analysis

To solve the problem that conventional MPSK recognition methods are inefficient under low SNR,a new modulation auto-recognition method based on Fast Independent Component Analysis(FICA) for MPSK signals was introduced.The method extracted the different signals component with FICA as the recognition feature for Maximum Likelihood PSK Classifier.It is proved that this algorithm adapts to recognize MPSK modulation under low SNR,distinguish signal and noise component effectively and has an excellent precision result.